Demo Data from VLDB 2026 / reviewers in the wild / expert
Jean-François Gobbers
dblp:39/5112
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › wavelet
wavelet design |
0.0 | 1 | 2002 | Directional dyadic wavelet transforms: design and algorithms · IEEE Trans. Image Process. 2002 |
Image and video processing
wavelet transform |
0.0 | 1 | 2002 | Directional dyadic wavelet transforms: design and algorithms · IEEE Trans. Image Process. 2002 |
Methods — techniques the papers use, named apart from their topics
l2 optimization · 0.0fourier domain implementation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Directional dyadic wavelet transforms: design and algorithmsabstractWe propose a simple and efficient technique for designing translation invariant dyadic wavelet transforms (DWTs) in two dimensions. Our technique relies on an extension of the work of Duval-Destin et al. where dyadic decompositions are constructed starting from the continuous wavelet transform. The main advantage of this framework is that it allows for a lot of freedom in designing two-dimensional (2-D) dyadic wavelets. We use this property to construct directional wavelets, whose orientation filtering capabilities are very important in image processing. We address the efficient implementation of these decompositions by constructing approximate QMFs through an L(2) optimization. We also propose and study an efficient implementation in the Fourier domain for dealing with large filters. Pierre Vandergheynst, Jean-François Gobbers |
IEEE Trans. Image Process. | 2 |